AI and Big Data for Optimized Water Resource Management in Arid Regions

Year : 2025 | Volume : 12 | Issue : 01 | Page : 1-5
    By

    Pratiksha Mahajan,

  • Minakshi Satpute,

  • Poonam Hanwate,

  • Amrapali Lokhande,

Abstract

Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper examines the role of AI, ML, and big data in advancing WRM, with a focus on irrigation optimization, desalination efficiency, and water distribution network management. AI and ML algorithms enable predictive modeling for demand forecasting, allowing for more efficient allocation of water resources. Additionally, big data analytics, leveraging Internet of Things (IoT) sensors and satellite imagery, provide real-time monitoring and comprehensive insights into water availability, usage patterns, and infrastructure performance. These technological advancements help optimize irrigation by analyzing soil moisture and climate conditions, improve desalination by enhancing energy efficiency and system reliability, and refine water distribution networks by detecting leaks and optimizing flow rates. Despite the potential benefits, challenges such as infrastructure limitations, data accessibility, high implementation costs, and the need for skilled personnel remain significant barriers to adopting AI-driven WRM solutions. This study addresses these challenges and proposes a strategic framework for integrating AI and big data into water management systems in arid regions. The findings aim to inform policymakers, engineers, and stakeholders on sustainable water management strategies, ensuring long-term resilience and resource security.

Keywords: Water resource management, artificial intelligence, big data, irrigation systems, desalination, water conservation, demand forecasting, arid regions, machine learning, sustainability

[This article belongs to Trends in Transport Engineering and Applications ]

How to cite this article:
Pratiksha Mahajan, Minakshi Satpute, Poonam Hanwate, Amrapali Lokhande. AI and Big Data for Optimized Water Resource Management in Arid Regions. Trends in Transport Engineering and Applications. 2025; 12(01):1-5.
How to cite this URL:
Pratiksha Mahajan, Minakshi Satpute, Poonam Hanwate, Amrapali Lokhande. AI and Big Data for Optimized Water Resource Management in Arid Regions. Trends in Transport Engineering and Applications. 2025; 12(01):1-5. Available from: https://journals.stmjournals.com/ttea/article=2025/view=209350


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Regular Issue Subscription Review Article
Volume 12
Issue 01
Received 09/01/2025
Accepted 02/01/2025
Published 04/02/2025
Publication Time 26 Days
Total Visits: 21


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